I read the full article. And it feels like much ado about nothing. One, the author for some reason is uncomfortable with a purely mathematical description of t

I read the full article. And it feels like much ado about nothing. One, the author for some reason is uncomfortable with a purely mathematical description of the world - without giving reasons beyond that humans cannot physically comprehend what the equations represent. Two, the whole piece disregards the advances in emergent phenomena, complex systems and statistics. Yes, we do not understand how individual electrons look like in copper, but statistical descriptions of copper dimensions, purity and grain size are enough to get an exceptionally accurate idea of the electrical behavior of a copper wire. This extends for exceptionally complex systems like lungs (smoking will significantly increase your cancer/emphysema risk), or planetary systems (increasing CO2 concentrations will increase surface temperatures). Three, There is also a weird bias against modeling. I am an experimental scientist, but I work closely with modellers, as all experimentalists do nowadays. Personally, I believe, that this bias against modeling often has a political component due to anthropogenic global warming. But in reality, there is a very vibrant dialogue between modellers and experimentalists, and hybrid scientists, people who are trained in both fields are the rage right now for hiring committees. Models have also improved dramatically - density functional theory is exceptionally accurate for smaller systems, while ReaxFF for dynamic systems and molecular dynamics simulations for more complex systems become better every year. The whole point about complex systems, applies to modelling too. I do not need to know the location of every molecule in the north Atlantic to predict the path of the hurricane - high pressure ridges and sea surface temperatures will give me really good results.